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This study examined the probability distribution that best described the quarterly economic growth rate of Nigeria between 1960- 2015. The study collected secondary data from Central Bank of Nigeria (CBN) Statistical Bulletin 2015 on Gross Domestic Product to compute the economic growth rate of Nigeria. Six theoretical statistical distributions were fitted via Normal Distribution, Logistic Distribution, Laplace Distribution, Cauchy Distribution, Gumbel (Largest Extreme Value) Distribution and Generalized Logistic Distribution. The Laplace Distribution fitted the data as confirmed by Kolmogorov Simonov goodness of fit test, Akaike Information Criteria and Bayes Information Criteria. The probabilities of economic growth rate behaviours were obtained from the best fit distribution. The analysis showed that the chance of obtaining a negative quarterly economic growth rate is 28%. The chance of an economic recession is 8%. Also, the probability of having a positive single digit quarterly economic growth rate is 46%. In addition, having a double digit positive quarterly economic growth rate is 26%.  

This research work studied the autoregressive integrated moving average (ARIMA) model that best fitted monthly stock market returns of the Nigerian Stock Exchange between January, 2008 to September, 2018. The study collected secondary data from Central Bank of Nigeria (CBN) Statistical Bulletin 2018 on monthly stock market index of NSE to compute the monthly stock market returns. The Box-Jenkins ARIMA modeling was adopted for this work. The series was tested for stationarity using Augmented Dickey Fuller test. Several ARIMA (p, d, q) models were applied to the monthly stock market returns to ascertain the best fit model for the series. The ARIMA (2, 0, 3) model was selected as the best fit for the data since it has minimum values of Akaike Information Criteria and Mean Squared Errors. The forecasted period showed a market with an unstable monthly stock market returns. Therefore, investors were advised to weigh the risks before venturing into the market to invest.

This research work focused on economic determinants that contribute to Commercial Banks Branches Expansion in Nigeria from 1988–2016 covering 29 years. This study used secondary data extracted from the Central Bank of Nigeria Statistical Bulletin, 2016 and the Poisson Regression Analysis was used in the analysis. Based on the analysis from this work, it was discovered that there was a strong relationship existing between commercial banks branches expansion, population growth rate, bank assets, savings deposit and gross domestic product growth rate. Therefore, this study concludes that population growth rate, bank assets, savings deposit and gross domestic product growth rate influence commercial banks branches expansion in Nigeria. Finally, a recommendation was made that commercial banks management should consider these factors- population size of the area of interest, the bank asset, savings deposit and economic activity of the area of interest before the location of a branch.

This research work, studied the hybrid of autoregressive integrated moving average (ARIMA) and generalized autoregressive conditional heteroscedasticity models that best fit monthly crude oil price volatility of Nigeria between January, 2010 to March, 2021. The study collected secondary data from quarterly Central Bank of Nigeria (CBN) Statistical Bulletin, June, 2021 on monthly crude oil price of Nigeria to compute the monthly crude oil price returns. The ARIMA-GARCH modeling was adopted for this work. The series was tested for stationarity using Augmented Dickey Fuller test. Several ARIMA -GARCH models were applied to the monthly crude oil price returns to ascertain the best fit model for the series. The ARIMA (2, 0, 5)-GARCH(1,4) model was selected as the best fit for the data since it has minimum values of Akaike Information Criteria and Mean Squared Errors. The forecasted period showed a crude oil price with an unstable monthly crude oil price returns. Therefore, the government of Nigeria was advised to be conservative when planning with revenue from crude oil sales in future.